Spinal cord injury (SCI) has attracted significant interest in the field of biomedical implants; its challenges range from matching the mechanical values of the host tissue to creating a scaffold capable of physically guiding the growing neurites. To date, no scaffold has yielded complete functional recovery, though recent attempts have managed to solve some, but not yet all, of the requirements for an effective scaffold. A historical summary of these efforts and related developments is presented below.
Cellular solids, being composites of a solid material and a gas phase, can be roughly divided into two broad categories: stretch-dominated structures and bending-dominated structures. Stretch-dominated structures are characteristically represented by honeycombs or lattice-like structures, while bending-dominated structures are characteristically represented by equi-axed foams consisting of open cell edges and cell faces [Ashby, 2005, Philosophical Magazine 85(26): 3235-3257]. Cellular solids are further characterized by their relative density: density of the cellular solid divided by the density of the fully-dense constituent materials. Failure of cellular foams can be broadly divided into three categories: plastic deformation, elastic buckling, and brittle fracture. In plastic deformation, the edges of the cell bend plastically, whereas elastomeric foams fail by elastic buckling. Brittle foams fracture at the cell edges. When plotting the material properties of cellular solids, the relative density often provides an intuitive and easy to manage means of comparing broad classes of materials. Typically, axially-loaded honeycombs (stretch-dominated lattices) perform better than equi-axed foams at the same relative density.
The processing of solutions and suspensions by the physical process of solidifying the solvent and removing it has been referred to as many things, including but not limited to: freeze casting, directional and uni-directional solidification, ice templating, and dendritic solidification. During solidification, the solubility of the solute is lower in the solid region than the liquid region; this inequality leads to solute being rejected from the propagating interface and accumulating. This boundary layer of solute changes the local concentrations, which in turn affects the liquidus temperature and creates a liquidus gradient across the boundary. When this liquidus gradient is higher than the temperature gradient formed by the freezing dendrite, the liquid is undercooled, also referred to as supercooled, as it is forced below its freezing temperature while remaining a liquid. This unstable region of supercooled liquid creates the driving force for ice-crystal formation, which propagate throughout the structure. If the overall thermal gradient is uniformly distributed, the ice-crystals will propagate in random directions, resulting in grain-like boundaries of ice. If, in the case of freeze casting, the temperature gradient is directional, then the region of constitutional undercooling will continue to push the ice-crystals in the same direction, creating a freezing front of dendrites. The growth of these dendrites is thus constrained by the undercooling conditions, which is in turn controlled by the temperature gradient; thus the freezing-front velocity of the dendrites is controlled by the rate of thermal diffusion. The rate of thermal diffusion is, in many freeze-casting systems in the art, controlled by controlling the temperature of a cold finger or cold source that the sample is placed in contact with and the cold-source's temperature is lowered at a steady rate, creating a uniform temperature gradient throughout the sample.
It has been reported that the freezing front of linearly aligned dendrites is only established once steady-state conditions have been reached, and two initial regions are observed prior to this steady state [Deville, et al., 2006, Biomaterials, 27(32):5480-5489].
Directly in contact with the cold source, the first zone (identified by Deville et al. in 2006) has little to no porosity, while the second has a uniform cellular morphology. The end of the second zone and the beginning of the third zone is characterized by the transition of the ice-crystals from a disperse cellular morphology to a linearly oriented morphology consisting of dendrites growing parallel to the thermal gradient [Deville, et al., 2006, Biomaterials, 27(32):5480-5489]. This was experimentally verified in-situ in 2009 by Deville et al., who used x-ray radiography to visualize the in-situ solidification of the third zone [Deville, et al., 2009, Journal of the American Ceramic Society 92(11): 2489-2496; Deville, et al., 2009, Journal of the American Ceramic Society 92(11): 2497-2503].
In 1954 Maxwell et al. reported on the freeze casting of thick slips of titanium carbide to make turbosupercharger blades. The researcher's aim was not to use this processing method to create highly porous structures, as most current biomedical applications require, but rather to generate high solid content slips that still retained oriented architectures, The opposite effect was accomplished 30 years later, when Ezekwo et al. and Tong et al. used directional freezing to structure highly porous aqueous agar gels [Tong, et al, 1984, Colloid & Polymer Science 262(7):589-595, Ezekwo et al., 1980, Water Research 14:1079-1088]. These gels exhibited the characteristic linearly oriented porosity of freeze-cast structures, as evidenced by both cross-sections and longitudinal slices. In 1985, Tong and Gryte analyzed the mass diffusion of the agar gels that they created and attempted to correlated the velocity of the freezing front to the resultant lamellae spacing.
More recently, freeze casting has received increased attention in three broad categories—ceramics, polymers, and metals, mostly for biomedical applications due to the inherently controlled architecture with porosity often in the range required for biological integration, Interest in ceramics revamped in the early 2000's, starting with filtration and catalyst applications [Fukasawa, et al., 2001, Journal of Materials Science 36(10):2523-2527; Fukasawa, et al., 2001, Journal of the American Ceramic Society 84(1):230-232; Fukasawa, et al., 2002, Journal of the American Ceramic Society 85(9): 2151-2155; Sofie, et al., 2001, Journal of the American Ceramic Society 84(7):1459-1464; Deville, et al., 2006, Science 311(5760):515-518]. With regard to biomedical applications, collagen has been particularly focused on, with recently some very promising attempts by Bozkurt et al. [Schoof, et al., 2000, Journal of Crystal Growth 209(1): 122-129; Schoof, et al., 2001, Journal of Biomedical Materials Research 58(4): 352-357; Bozkurt, et al., 2007, Tissue Engineering 13(12):2971-2979; Bozkurt, et al., 2009, Biomaterials 30(2):169-179], Metals represent the newest class of materials that have been freeze cast, and titanium scaffolds have opened a new range of material properties achievable for such high porosities [Chino, et al., 2008, Acta Materialia, 56(1):105-113; Yook, et al., 2008, Materials Letters 62(30):4506-4508].
In 1985, H. M. Tong and C. C. Gryte presented a theory for predicting the size of lamellar ice crystal sheets resulting from steady-state unidirectional freeze casting of aqueous agar. They compared their model against varying concentrations of agar solidification and subsequent lyophilization, and found that the model could not predict the changes when the solution was increased from 3% to 10% by weight.
Tong and Gryte considered a hypothetical interface approximated by a trigonometric function as opposed to the actual finger-like dendritic extension micrographed by Bozkurt et al. in 2009 [Bozkurt, et al., 2009, Biomaterials 30(2):169-179; Tong, et al., 1985, Colloid & Polymer Science 263(2):147-155]. They defined λ as the lamellar spacing, and set the trigonometric function to z=p0 cos(wx) where p0 is the amplitude of the function (and of the ice tips) and
      λ    =                            2          ⁢          π                ω            =                        L          0                n              ,where n is the number of crystal tips along L0 minus 1.
With respect to the mass transfer analysis of the situation, Tong and Gryte defined the continuity equation as equation (1), subject to boundary conditions (2) through (5), where is the agar concentration, V is the freezing-front velocity of the ice-crystals, and D is the diffusion coefficient. In essence, these boundary conditions are as follow: The concentration of the solution at z=∞ is that of the bulk agar concentration, and the change in concentration with respect to x (perpendicular to the ice-crystal growth front) is zero at the center of each ice-crystal. They defined the change in concentration along the propagating ice-crystal freezing front (the z-direction) as equation (4) at point T (the tip of the ice-crystal) and zero (with C=Cg) at point V (the nadir of the trigonometric function, representing the fully vitrified agar solution). Cg, the agar concentration of the vitrified solution, was taken to be 50%, as previously determined [Tong, et al., 1985, Colloid & Polymer Science 263(2):147-155].
                                                                        ∂                2                            ⁢              C                                      ∂                              z                2                                              +                                                    ∂                2                            ⁢              C                                      ∂                              x                2                                              +                                    (                              V                D                            )                        ⁢                          (                                                ∂                  C                                                  ∂                  z                                            )                                      =        0                            (        1        )                                C        =                                            C              g                        @            z                    =          ∞                                    (        2        )                                                      ∂            C                                ∂            x                          =                              0            @            x                    =                      0            ⁢                                                  ⁢            and            ⁢                                                  ⁢                          π              ω                                                          (        3        )                                                      ∂            C                                ∂            z                          =                                            -                              (                                  V                  D                                )                                      ⁢                          (                              1                -                                  k                  0                                            )                        ⁢            C                    =                                    -                              (                                  V                  D                                )                                      ⁢                                          C                T                            @              point                        ⁢                                                  ⁢            T                                              (        4        )                                                      ∂            C                                ∂            z                          =                              0            ⁢                                                  ⁢            and            ⁢                                                  ⁢            C                    =                                                    C                g                            @              point                        ⁢                                                  ⁢            V                                              (        5        )            
In order to analyze the solute concentration ahead of the hypothetical interface, Tong and Gryte divided the concentration into two terms—the first a composition averaged across the interface (c0) that is only a function of the z-direction (freezing direction) and the second a radial component that is a function of both x and z directions (c1). See equation (6), where
  ω  =            λ              2        ⁢        π              .  Using a first-order approximation (n=1), Tong and Gryte were able to analytically solve for the constants a and h as functions of the concentration, freezing front velocity, diffusion constant, and physical parameters. They were thus able to derive a relationship between p0 and λ—equation (7)—where
  ω  =            λ              2        ⁢        π              .  
                                          C            ⁢                          ⌊                              x                .                z                            ⌋                                =                                                    C                0                            ⁢                              ⌊                z                ⌋                                      +                                          C                1                            ⁢                              ⌊                                  x                  ,                  z                                ⌋                                                    ⁢                                  ⁢                                            Where              ⁢                                                          ⁢                              C                0                            ⁢                              ⌊                z                ⌋                                      =                                          C                b                            +                              λ                ⁢                                                                  ⁢                                  ⅇ                                      ⌊                                                                  -                        vz                                            D                                        ⌋                                                                                ,                                          ⁢                                                    C                1                            ⁢                              ⌊                                  x                  ,                  z                                ⌋                                      =                                          ∑                                  n                  =                  1                                ∞                            ⁢                                                a                  n                                ⁢                                  ⅇ                                                            ⌊                                                                        -                                                      ω                            n                                                                          ⁢                        z                                            ⌋                                        ⁢                    cos                    ⁢                                          ⌊                                              n                        ⁢                                                                                                  ⁢                        ω                        ⁢                                                                                                  ⁢                        x                                            ⌋                                                                                                    ,          and                ⁢                                  ⁢                              ω            n                    =                                    v                              2                ⁢                D                                      +                                                                                (                                          V                                              2                        ⁢                        D                                                              )                                    2                                +                                                      n                    2                                    ⁢                                      ω                    2                                                                                                          (        6        )                                          p          0                =                              ln            ⁡                          (                                                                    c                    g                                                        c                    b                                                  -                1                            )                                            2            ⁢                          ω              1                                                          (        7        )            
It is interesting to note, then, that the solution to the mass-diffusion differential equations can be defined by two dimensionless parameters:
      (          λ              p        D              )    ⁢          ⁢  and  ⁢          ⁢            (                        λ          ⁢                                          ⁢          V                D            )        .  in order to develop a relationship between the lamellar spacing and the diffusion constant and the freezing front velocity, two different approaches were taken, arriving at two different relationships between p0 and λ.
The first, more complicated and more accurate method involved analysis of the lowest free energy criterion, wherein it was noted that no significant amount of undercooling was needed for the propagation of the ice crystals, and that therefore equilibrium conditions are established at the freezing front. Analysis of the free energy of the system led to equation (8), which establishes a relationship between p0 and λ.
                                          Δ            ⁢                                                  ⁢                          G              total                                =                                                    (                                                      σ                    ⁢                                                                                  ⁢                                          L                      0                                                        π                                )                            ⁢              I              ⁢                              ⌊                ω                ⌋                                      +            constant                          ⁢                                  ⁢                              Where            ⁢                                                  ⁢            I            ⁢                          ⌊              ω              ⌋                                =                                    ∫              0              π                        ⁢                                                            1                  +                                                            p                      D                      2                                        ⁢                                          ω                      2                                        ⁢                                          sin                      2                                        ⁢                                          ⌊                      y                      ⌋                                                                                  ⁢                              ⅆ                y                                                                        (        8        )            
The second, more elegant, albeit less accurate method used Einstein's diffusion theory to relate the time for a molecule to move a distance
      λ    2    ,or
      π    ω    ,to the effective diffusion coefficient D. Physically, then, this is the time that it takes the molecules to move from the tip of the ice-crystal to the center of the vitrified region. This distance is by definition 2p0, and with V being the velocity of ice the time is thus
            2      ⁢              p        0              V    .These two times must be equal to avoid agar build-up between the propagating ice-crystals, and thus solving for p0 as a function of lamellar spacing λ yields equation (9).
From empirical testing of p0 and λ, Tong and Gryte saw that the ratio of
  λ      p    0  remains constant throughout the freezing process across varying velocities, and that therefore equation (9) reduces to simply
                    V        ⁢                                  ⁢        λ            D        =    Constant    ,which for a constant diffusion coefficient reduces to Vλ=Constant.
                              p          0                =                                            V              ⁢                                                          ⁢                              π                2                                                    4              ⁢              D              ⁢                                                          ⁢                              ω                2                                              =                                    V              ⁢                                                          ⁢                              λ                2                                                    16              ⁢              D                                                          (        9        )            
When analyzing these assumptions and comparing them against the literature and other models, several key differences are noticed which could account for the inability to accurately predict the lamellar spacing.
Other equations have been proposed that suggest the linear relationship
      λ    ∝          1              V        n              ,where n is between 1 and 4 [Butler, 2001, Crystal Growth & Design 1(3): 213-223; Deville, et al., 2007, Acta Materialia 55(6):1965-1974].
The majority of freeze-cast polymers to date have been collagen or collagen-combinations, though chitosan has of recent been gaining more attention. Some of the more comprehensive reports have been by Bozkurt et al., who froze collagen for biomedical applications.
In an intact spinal cord, afferent neurons project through interneurons to motor neurons within the gray matter, which send axons out through the dorsal root ganglions to the peripheral nervous system (PNS). Conversely, primary sensory neurons project axons through the PNS to the gray matter in the central nervous system (CNS), where they are transferred to the white matter and directed to supraspinal areas. Lipid-derived myelin coating of the axons allows for saltatory nerve conduction, in which action potentials leap from sequential nodes of Ranvier. This coating is performed by oligodendrocytes in the CNS and Schwann cells in the PNS.
The heterogeneous nature of spinal cord injury (SCI) leads to varied endogenous responses, and can be caused by contusion, compression, or penetration of the spinal cord [Thuret, et al., 2006, Nat Rev Neurosci 7(8): 628-643]. Contusions frequently generate cysts, consisting of astrocytes, progenitor cells, and microglia. Penetrating injuries generally allow for PNS cells to infiltrate and form scar tissue, which is usually formed from fibroblasts, Schwann cells, and various reactive glia. Either of these processes usually interrupts both ascending and descending neuronal tracts, and are detrimental to oligodendrocytes, neuroglia, and precursor cells [Horkey, L. L., et al., 2006, The Journal of Comparative Neurology 498(4):525-538], while any disconnected axons segments are phagocytosed by macrophages [Thuret, et al., 2006, Nat Rev Neurosci 7(8): 628-643]. Following the initial injury, active secondary processes occur, which have been attributed to apoptosis, Ca2+ influx, plasma membrane disruption, and lipid peroxidation. Apoptotic cells positively expressing oligodendrocyte markers were seen from 6 hours up to 3 weeks [Crowe, M. J., et al., 1997, Nat Med 3(1):73-76], and chronic resulting demylinated axons have been found at the site of injury up to 10 years post-trauma [Guest, et al., 2005, Experimental Neurology 192(2):384-393].
Some of the first quantitative measurements of the spinal cord modulus were performed in the late 1970's at the University of Oregon Health Sciences, Center, and in the early 1980's at the University of Pittsburgh. Archie R. Tunturi, M. D., working in Oregon, measured specifically the spinal cord dura matter in dogs, while the researchers at the University of Pittsburgh sought to test the mechanical properties of the neuronal column itself [Tunturi, A. R., 1977, Journal of Neurosurgery 47(3):391-396]. Three papers resulted from these initial experiments; two on cats, and one on puppies. In all cases, the subjects were anesthetized and mounted within an Instron tensile testing device. Ring clamps were mounted on the subjects' exposed spinal cords, which were then stripped of the dura matter. It is, however, critical to note that by only removing the dura matter, the researchers were testing a combination of pia, gray, and white matter. This is a key distinction to make note of, as the neuronal cells interact with the gray and white matter, but not the pia mater; thus any scaffolds designed to match the mechanical properties need to match those of the gray and white, not the combination of those with the pia mater. By performing these experiments in-situ on anesthetized subjects the researchers avoided changing physiological conditions incurred by death. To avoid dehydration, upon exposure of the spinal cord the researchers housed the test section in a polymer container, and filled the reservoir with Normosol, an isotonic solution of electrolytes as a substitute for the native cerebrospinal fluid [Hung, T.-K., et al., 1981, Journal of Biomechanics 14(4): 269-276].
A more detailed testing procedure was carried out by Bilston and Thibault in 1995, wherein they tested cervical sections of human cadavers. A quasilinear viscoelastic model was arrived at; however, specific moduli for different strain rates were reported, and one can see that the moduli were approximately 1 MPa [Bilston, L. et al., 1995, Annals of Biomedical Engineering 24(0):67-74]. Again, however, Bilston and Thibault reported removing the dura matter but specifically leaving the pia, gray, and white matter. Also, the samples were harvested up to 12 hours post-mortem, which has been suggested to dehydrate and stiffen the native tissues [Bilston, L. et al., 1995, Annals of Biomedical Engineering 24(0):67-74; Ozawa, H., et al., 2004, J Neurosurg Spine 1(1):122-7]. This explains the significantly higher modulus reported by Bilston and Thibault, as compared to Ozawa et al. in 2004, who measured specifically the Pia mater by itself, the gray and white matter by themselves, and the gray and white matter with the Pia mater left attached. Ozawa et al. found that the Pia mater by itself had a Young's modulus of 2.3 MPa, and when left intact and wrapped around the gray and white matter, it effectively tripled the modulus from 5 to 16 kPa. Unfortunately, the researchers tested the Pia mater itself in tension, and then tested gray and white matter, and the gray/white/Pia combination, in compression, which may explain why the Pia mater, with a Young's modulus of 2.3 MPa in tension, only tripled the compressive modulus of the gray/white/Pia combination to 16 kPa. The researchers also performed a series of cross-sectional compression analyses with and without the Pia mater and concluded that the Pia mater, along with the dura matter, is largely responsible for producing a strain energy on the gray and white matter, which is responsible for maintaining the shape and circumference upon compression.
In 2001, Ozawa et al, performed some of the first mechanical testing on specifically the gray and white matter in-situ. To avoid any post-mortem changes in physiology, they performed their tests within one hour of sacrificing the subjects (cats). They excised the spinal cord segments, removing both dura and pia mater, and sliced the remaining gray and white matter so as to expose either sagittal, axial, or frontal planes. Mechanical testing was performed via pipette aspiration, whereby a glass pipette was placed perpendicular to the substrate, and negative pressure applied via a reservoired vacuum pump. Deformation was measured by a video microscope, and a video dimension analyzer was used to determine the aspirated length of the substrate. Their findings were, expectedly, in close agreement with mechanical testing performed on brain parenchyma [Ozawa, H., et al., 2001, Journal of Neurosurgery: Spine 95:221-224].
The importance of these studies becomes rapidly event when trying to match the mechanical values of a neuronal scaffold to those of the native tissues. Many of the mechanical values reported in the literature only report on an ill-defined “spinal cord's” Young's modulus, and it is only through a thorough investigation of the literature, along with knowledge of the spinal cord anatomy, that one realizes that many of the reported values are not those of the tissues that the neurons actually interact with. One of the first research groups to accurately cite the correct values was headed by Bakshi et al. [Bakshi, A., et al., 2004, Journal of Neurosurgery: Spine 1(3)322-329]; they were able to achieve a hydrogel scaffold of appropriate stiffness.
The importance of matching substrate stiffness has been receiving growing recognition in recent reviews [Madigan, N., et al., 2009, Respiratory Physiology & Neurobiology 169(2):183-199], and for neuronal growth was specifically tested and proven in 2009 by Leipzig and Shoichet [Leipzig, N. et al., 2009, Biomaterials 30(36):6867-6878]. To create a substrate of specific mechanical stiffness, a photopolymerizable methacrylamide chitosan (MAC) was developed, the modulus of which could be directly tuned from the amount of photo-induced crosslinking. Three scaffolds of varying moduli were created, resulted in E=0.8±0.18, 3.59±0.51, and 6.72±0.58 kPa, herein referred to simply as 1, 3.5, and 7 kPa. In order to achieve a more robust cell attachment, the researchers coated their chitosan scaffolds with laminin, a protein family found in the basil lamina. Neural stem/progenitor cells (NSPCs) were harvested from adult subventricular zones and cultured on the various substrates; examined were the differentiation of the NSPCs into the three main cell types of the neuronal cord: neurons, oligodendrocytes, and astrocytes. Cell differentiation and proliferation for neurons were shown to be highest when E=3.5 kPa, consistent with the measured gray and white matter mechanical values by Ozawa et al. in 2001. Oligodendrocyte maturation was shown to be highest on the softest substrates, although cell differentiation was highest on the 7 kPa. The researchers justified this difference in cell maturity and differentiation by explaining that in the presence of increased neuronal growth, the oligodendrocytes would exhibit more mature features, as they had more neurons to ensheath. Leipzig and Shoichet also created substrates with moduli greater than 10 kPa, upon which the NSPCs neither proliferated nor differentiated.
Significant numbers of polymeric scaffolds for spinal cord regeneration of particular mechanical values and/or particular geometries have been created over the years. One of the first papers to recognize the importance of matching mechanical strengths—and realize what the correct mechanical values are—was the previously mentioned paper by Bakshi et al. in 2004. The authors created poly(2-hydroxyethylmethacrylate) (pHEMA) hydrogels with 85% water content and interconnected pores 10 to 20 μm in diameter. When soaked in simulated physiological conditions, the scaffolds had compressive moduli of 3 to 4 kPa, which aligns well with the previously mentioned values. They performed a partial cervical hemisection, peeling back the dura mater and implanting the scaffold before closing the flap of dura and suturing. The authors soaked the pHEMA in brain-derived neurotrophic factor (BDNF) and saw that up to 2 weeks the BDNF-soaked scaffolds promoted significant axonal regeneration and growth into the scaffold. Unfortunately, after the two weeks the axonal growth regressed, most likely due to the BDNF diffusing away, since the authors did allow that unmodified pHEMA was not suitable for axonogenesis [Bakshi, A., et al., 2004, Journal of Neurosurgery: Spine 1(3):322-329].
Aside from BDNF, a host of other growth factors have been similarly used, such as ciliary neurotrophic factor (CNTF), which plays a role in motor neuron growth and survival, fibroblast growth factors (FGFs), which indirectly help by inducing angiogenesis and directly have been shown to promote axon outgrowth, and glial derived neurotrophic factor (GDNF), which is secreted by Schwann cells after injury and is structurally similar to transforming growth factor β (TGF-β), which may be useful for coating neural implants [Willerth, S. et al., 2007, Advanced Drug Delivery Reviews 59(4-5):325-338]. Schwann cells in particular have been used in many of the more promising experiments, and have been incorporated into a variety of scaffold and scaffold-like containers. In 1999, Xu et al. seeded Schwann cells in Matrigel, an extracellular-like matrix of proteins secreted by mouse sarcoma cells. It was claimed that due to an inherent “syneresis” effect of Matrigel, a cable of aligned Schwann cells formed over 24 hours, though they provided no proof. The Matrigel seeded matrix was placed inside a spun 60:40 acrylonitrile:vinylchloride (PAN/PVC) copolymer which was capped at either ends with a glue of PAN/PVC. The presence of Schwann cells induced up to 105 axons to enter the graft; a result that is not atypical with Schwann cell seeded grafts [Xu, X. M., et al., 1999, European Journal of Neuroscience 11(5):1723-1740; Oudega, M., et al., 2001, Biomaterials 22(10):1125-1136].
Hydrogels are, arguably, the most common scaffolds used for attempted spinal cord reparation. They are generally water-insoluble polymer networks that are highly porous and typically have water contents greater than 90 percent. pHEMA [Dalton, P. D., et al., 2002, Biomaterials 23(18):3843-3851; Bakshi, A., et al., 2004, Journal of Neurosurgery: Spine 1(3):322-329] and poly N-2-(hydroxypropyl)methacrylamide (PHPMA) [Woerly, S., et al., 2001, Biomaterials 22(10):1095-1111; Woerly, S., et al., 2001, Journal of Neuroscience Research 66(6):1187-1197] are two such hydrogels used as scaffolds for SCI. The biggest drawback of hydrogels is their isotropic nature. While they may be highly porous, their physical structure does not lend itself to aligned growth.
Because of this drawback to hydrogels, many researchers have attempted to generate linearly oriented scaffolds so as to physically guide the growing axons. Teng et al. in 2002 used a poly(lactic-co-glycolic acid) (PLGA) blend to generate axially oriented pores by unidirectionally freezing a solution of PLGA and subliming the solvent. The freezing was produced by lowering the solution into an ethanol/dry ice bath, which created both longitudinal and radial porosity [Teng, Y. D., et al., 2002, Proc Nat Acad Sci USA 99(5):3024-3029]. Another attempt at induced growth by linearly aligned contact guidance was done in 2003 by Yoshii et al. who used bundled collagen filaments to provide linearly oriented cables along which the nerve cells could grow. After 8 weeks in vivo axon growth extended 20-24 millimeters into the graft. The collagen filaments averaged 20 μm in diameter, and both 2000 and 4000 bundled filament grafts were used. Unfortunately, no mention of how tightly compressed or cross-section images of the filaments were reported; thus knowledge of the substrate that the axons were growing on is lacking. A similar attempt was made by Stokols et al. in 2004 when they placed dissolved agarose on top of a pool of liquid nitrogen; the linear ice crystals were then sublimed away.
The average pore diameter was 119 μm, and the walls of the pores were smooth. While the morphology of the scaffolds is approaching that of a well-designed scaffold, the authors failed to recognize the importance of matching the mechanical properties of the scaffold. Their only mention was that the hydrated scaffold was “soft and flexible,” possessing mechanical properties “hypothetically advantageous for use in the spinal cord.” A nerve growth factor was incorporated into the scaffold, and PC12 cells were cultured successfully, demonstrating the feasibility of the agarose scaffolds [Stokols, et al., 2004, Biomaterials 25(27): 5839-5846].
In 2005, Mahoney et al. attempted a systematic approach to linearly guiding neurite growth by creating channels on a photosensitive polyimide (PSPI). The walls of the channels were 11 μm high and 10 μm wide, while the width of the channel ranged from 20 μm to 60 μm, in steps of 10 μM. PC12 cells were terminally differentiated with NGF and seeded along the patterned chips for 3 days. The length, number of neurites exiting each soma, and angle of neurite to the channel wall were all measured. The neurites often grew towards the channel walls, and then continued in roughly a straight line. It was seen that in the control PC12 cells, which were seeded on flat unpatterned chips, the number of exiting neurons were twice that of those exiting the 20 μm wide channels; however the 20 μm wide channels had the longest neurites. Unfortunately, the authors did not create channels less than 20 μm wide, so there is it not known whether 15 or 10 μm wide channels would generate longer neurites.
Another attempt to linearly guide neurites by growing them along channels was performed by Zhang et al. in 2005. Using wet phase inversion they created hollow fiber membranes out of PLGA with textured inner diameters that had grooves running parallel to the axis of the hollow membrane. Dorsal root ganglions (DRGs) were seeded at one end of the membrane and cultured for 7 days. [Zhang, et al., 2005, Journal of Biomedical Materials Research Part A 75A(4):941-949].
Johansson et al. analyzed sub-micron channel guidance of neurites, using nanoimprint lithography to generate PMMA substrates with 300 nm deep channels of varying width (100 to 400 nm) and varying distance between channels (100-1600 nm). These channels were roughly an order of magnitude smaller than the two previously mentioned studies, and the channels were approximately on the same scale as the extending neurites themselves. The authors reported on a “wandering behavior” of the axons at that scale, and stated that the axons had a tendency to branch back and forth across several ridges, despite maintaining an overall linear growth. SEM images show that the axons grew on the top of the ridges, as opposed to inside the larger channels of Mahoney et al.'s substrates. The SEM images also showed a significantly scattered growth pattern of neurites, to the point where the authors used a Fourier transform to quantify the amount of guidance. Results from their experiments show that nano-scale channels are capable of aligning axons, although the SEMs suggest that the channels were too small to cause any more than general alignment; significant bridging and wandering of the axons can be seen, and their results suggest no clear trend in either channel width or spacing for optimal alignment.
Two of the most impressive papers on spinal cord repair scaffolds were produced by Bozkurt et al. in 2007 and 2009 [Bozkurt, et al., 2007, Tissue Engineering 13(12):2971-2979; Bozkurt, et al., 2009, Biomaterials 30(2):169-179]. Based in Aachen, Germany, the group used freeze casting to general linearly oriented porcine collagen scaffolds with pore diameters of 20 to 50 μm. Biopsy punches were used to generate cylinders of scaffold. DRGs were harvested from Lewis rats and sliced in half; the sectioned surface was then placed on the cross-section surface of the scaffolds and cultured for 21 days. In-vitro analysis was performed using fluorescent light microscopy and confocal laser microscopy.
In 2009 the same group of researches varied the amount of crosslinking within the same freeze-cast collagen scaffolds and seeded the scaffolds with Schwann cells. Crosslinking was achieved with 1-ethyl-3(3-dimethylaminopropyl)carbodiimide (EDC). Gamma irradiation sterilized said scaffolds, and the degree of crosslinking was determined by spectrophotometrically measuring the free amine group content. Immunocytochemistry of the Schwann cells shows linear alignment of the Schwann cells.
Thus, there is a long felt need in the art for a freeze cast polymer scaffold for targeted neuronal growth and repair, as well as a process for controlling freeze casting such that the morphology and mechanical features of the scaffold can be customized and selected for. The present invention satisfies this need.